Generally, it can be said that analyzing focus group data is not much different from the analysis of any other kind of interview data. Most people who ask for specific analytic tools in focus groups do so because they don't have experience with analyzing other kinds of qualitative data, so they think there must be something unique about focus groups.
Focus groups are different to a certain extent as there is more interaction. In the vast majority of studies, researchers are interested in the content of what gets said, rather than the mechanics of how it gets said.
If you are interested in the interaction, then a discourse analysis might be an appropriate method. In addition to the regular tools you use in ATLAS.ti for data analysis, consider using hyperlinks to explore the interaction Quotation Level and Hyperlinks.
The most widely used analysis methods for interview as well as focus group data are versions of content analysis and thematic analysis. For some inspiration, take a look at this chapter on focus group analysis.
ATLAS.ti facilitates the coding of speaker units, so that you can compare responses of different speakers or different group of speakers by attributes like age, gender, etc.
In order for ATLAS.ti to recognize speakers, you need to use speaker IDs or names consistently when transcribing the data. See Guidelines for Preparing Focus Group Data for more detail.
Focus group auto coding requires text documents in doc, docx, rtf, or txt format. You cannot use PDF documents with this function.